Our case study work on how to preserve and reproduce a high energy physics (HEP) application with Parrot has been accepted by Journal of Physics: Conference Series (JPCS 2015).
The HEP application under investigation is called TauRoast, and authored by our physics collaborator, Matthias. TauRoast is a complex single-machine application having lots of implicit and explicit dependencies: CVS, github, PyYAML websites, personal websites, CVMFS, AFS, HDFS, NFS, and PanFS. The total size of these dependencies is about 166.8TB.
To make TauRoast reproducible, we propose one fine-grained dependency management toolkit based on Parrot to track the really used data and create a reduced package which gets rid of all the unused data. By doing so, the original execution environment with the size of 166.8TB is reduced into a package with the size of 21GB. The correctness of the preserved package is demonstrated in three different environments - the original machine, one virtual machine from the Notre Dame Cloud Platform and one virtual machine from the Amazon EC2 Platform.
| Haiyan Meng, Matthias Wolf, Peter Ivie, Anna Woodard, Michael Hildreth and Douglas Thain, A Case Study in Preserving a High Energy Physics Application with Parrot, Journal of Physics: Conference Series, December, 2015. |
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